Data and code for the publication entitled: tree growth and mortality of 42 timber species in Central Africa

[Lien vers la fiche source] # Introduction This archive contains all the necessary data and R script to reproduce the results of the manuscript entitled "tree growth and mortality of 42 timber species in Central Africa" submitted to Forest Ecology and Management journal. It includes cleansed data (text files and Rdata files), computed data (estimates of tree growth and mortality rates, Rdata files), R script to reproduce the computation of the estimates as well as the analyses and figures presented in the main paper and an excel files containing all the supplementary material tables of the manuscript. # Cleansed data To produce the cleansed data, raw data was collected for each sites. The different datasets were standardized to store all of them in a single database. Next, consecutive diameter measurements were analyzed and some outliers were discarded (see the explanations in the main manuscript). The cleansed data can be loaded using either text delimited csv files or a Rdata file. It contains the five following tables. ## Table cleansed_data _species‧csv This table contains information about each study species. Each line corresponds to one species. It contains the following columns: * code : species identifying name * timber_name : species name as used by the ATIBT * species_name_sci : current scientific species name (genus + species) * species_name : vernacular species name * dme : reference value of the minimum cutting diameter as defined by the Cameroonian Government * incr : reference value of diameter increment (cm/year) as defined by the Cameroonian Government * cjb_id : species id of the [CJB database] * see_name : species CJB id of synonym names * species_name_sci_full : full current scientific name (genus + species + authority) ## Table cleansed_data _observation_codes‧csv This table contains the description of the codes used in the field to note any particularities of the monitored trees. One line correspond to one code. There are three columns: * code : observation code * label_fr : French explanation of the code (as used in the field) * label_en : English translation of the explanation of the code ## Table cleansed_data _mortality_codes‧csv This table contains the description of the codes used to characterize the likely cause of recorded tree death. There are three columns: * code : mortality code * label_fr : French explanation of the code (as used in the field) * label_en : English translation of the explanation of the code ## Table cleansed_data _records‧csv This table contains the information collected for each tree. Each line corresponds to one record for one tree. There are several lines per tree as they were measured several times. It contains the following columns: * site : site name * id_site : site identifying number * id_plot : plot identifying number * treatment : treatment (control, exploited or mixed). * exploitation_year : year of the exploitation (4 digits) * species : species vernacular name (corresponding to species_name column of species table) * id_tree : tree identifying number * number : tree number (the number that was painted on the tree) * id : record identifying number * date : record date (yyyy-mm-dd) * census_year : year of the census * diameter : tree diameter measured at hom (cm) * diameter450 : tree diameter measured at 450 cm in height (cm) * hom : height of measurement of the diameter (cm) * code_observation : observation codes. Multiple codes were sometimes used. They are separated by a dash (corresponding to code column of observation_codes table). * code_mortality : mortality codes (corresponding to code column of mortality_codes table) * comment : any additional comment ## Table cleansed_data _Increments‧csv * id : id of the initial measurement * id_tree : tree id number * id_plot : plot id number * treatment : treatment (control, exploited) * species : species vernacular name (corresponding to species_name of species table) * number : tree number (the number that was written on the tree) * hom : height of measurement (cm) * id_hom : id of HOM (sometimes the HOM had to be changed, e‧x. due to buttresses or wounds) * initial_date : date of the first census * initial_diameter : the diameter measured at the first census (cm) * diameter_increment : The annual diameter increment computed between the two considered census (cm/year) * increment_period : The number of years separating the two censuses (years) * diameter_observation : Observation codes (corresponding to code of table observation_codes) that were noted during the first and second census. The observation of the two censuses are separated by a “/”. * diameter_comment : Additional comments written during the two measurements. They are separated by a “/”. * Id_species : species identifying number * Id_site : site identifying number * Site : name of the site * Exploitation_year : year of the exploitation (if any) ## File cleansed_data.Rdata This Rdata file contains the five tables (species, mortality_codes, observation_codes, records and increment) of the cleansed data It can be used to rapidly load in R. # Computed data From the cleansed data, we computed - as explained in the main manuscript - tree growth and mortality rates using an R script (3-computation.R). This script produces “computed data”. The computed data contains six tables that are provided with three additional csv files and one RData files. ## Computed_data_records‧csv This table is the same as record‧csv but with one additional column: * exploitation_date : the assumed date of the exploitation if any (yyyy-mm-dd) ## Table computed_data_growth_rates‧csv This table contains one line per combination of tree and treatment. It contains the estimates of diameter increment computed over all available records. This table contains the following columns: * site : site name * id_site : site identifying number * treatment : treatment (control or exploited) * species : species vernacular name * id_plot : plot id number * id_tree : tree id number * initial_diameter : tree diameter at the begining of the census period (cm) * increment_period : length of the census period (year) * initial_date : date of the first census (yyyy-mm-dd) * diameter_observation : observation codes if any * diameter_comment : comment if any * exploitation_year : year of the exploitation (4 digits) * exploitation_date : assumed date of the last exploitation (if treatement = logged or mixed) * mid_point : mid-point of the census period (yyyy-mm-dd) * years_after_expl : length of time between the exploitation date and the first measurement * n_increment : number of consecutive increment * n_hom : number of change of hom during the census period * diameter_increment : estimate of the diameter increment (cm/year) ## Table computed_data_mortality_rates‧csv This table contains estimates of mortality rates for each species and site. This table contains the following columns: * id_site : site id number * treatment : treatment (control or exploited) * time_min : minimum of the length of the census periods * time_max : maximum of the length of the census periods * time_sd : standard deviation of the length of the census periods -- deleted * exploitation_year : exploitation year (if treatment = exploited) * years_after_expl_mid : number of years between the assumed exploitation and the mid-period census. * years_after_expl_start : number of years between the assumed exploitation and the first census. * site : site name * species : species vernacular name * N0 : number of monitored trees * N_surviving : number of surviving trees * meantime : mean monitoring period length * rate : estimates of the mortality rate * lowerCI : lower bound of the confidence interval of the mortaltity rate * upperCI : lower bound of the confidence interval of the mortaltity rate ## File computed_data.Rdata This Rdata file contains the six tables (species, records, growth_rates, mortality_rates, mortality_codes, observation_codes) of the computed data. It can be used to load them in R. # Analyses The analyses presented in the main manuscript were produced with a Rmd script (4-analyses.Rmd). This script generates an HTML report (4-analyses.html), as well as the figure that are shown in the manuscript and an Excel file with all the supplementary tables (with one sheet per supplementary table).